7e9a772104
✨ 主要优化成果： - 修复Unicode字符编码问题（Windows跨平台兼容性） - 安装wkhtmltoimage，截图功能完全修复 - 智能延迟优化（api_browser.py） - 线程池资源泄漏修复（tasks.py） - HTML解析缓存机制 - 二分搜索算法优化（kdocs_uploader.py） - 自适应资源配置（browser_pool_worker.py） 🐛 Bug修复： - 解决截图失败问题 - 修复管理员密码设置 - 解决应用启动编码错误 📚 新增文档： - BUG_REPORT.md - 完整bug分析报告 - PERFORMANCE_ANALYSIS_REPORT.md - 性能优化分析 - LINUX_DEPLOYMENT_ANALYSIS.md - Linux部署指南 - SCREENSHOT_FIX_SUCCESS.md - 截图功能修复记录 - INSTALL_WKHTMLTOIMAGE.md - 安装指南 - OPTIMIZATION_FIXES_SUMMARY.md - 优化总结 🚀 功能验证： - Flask应用正常运行（51233端口） - 数据库、截图线程池、API预热正常 - 管理员登录：admin/admin123 - 健康检查API：http://127.0.0.1:51233/health 💡 技术改进： - 智能延迟算法（自适应调整） - LRU缓存策略 - 线程池资源管理优化 - 二分搜索算法（O(log n) vs O(n)） - 自适应资源管理 🎯 项目现在稳定运行，可部署到Linux环境
589 lines
22 KiB
Python
Executable File
589 lines
22 KiB
Python
Executable File
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""截图线程池管理 - 工作线程池模式（并发执行截图任务）"""
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import os
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import threading
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import queue
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import time
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from typing import Callable, Optional, Dict, Any
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# 安全修复: 将魔法数字提取为可配置常量
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BROWSER_IDLE_TIMEOUT = int(os.environ.get("BROWSER_IDLE_TIMEOUT", "300")) # 空闲超时(秒)，默认5分钟
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TASK_QUEUE_TIMEOUT = int(os.environ.get("TASK_QUEUE_TIMEOUT", "10")) # 队列获取超时(秒)
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TASK_QUEUE_MAXSIZE = int(os.environ.get("BROWSER_TASK_QUEUE_MAXSIZE", "200")) # 队列最大长度(0表示无限制)
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BROWSER_MAX_USE_COUNT = int(os.environ.get("BROWSER_MAX_USE_COUNT", "0")) # 每个执行环境最大复用次数(0表示不限制)
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# 新增：自适应资源配置
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ADAPTIVE_CONFIG = os.environ.get("BROWSER_ADAPTIVE_CONFIG", "1").strip().lower() in ("1", "true", "yes", "on")
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LOAD_HISTORY_SIZE = 50 # 负载历史记录大小
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class AdaptiveResourceManager:
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"""自适应资源管理器"""
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def __init__(self):
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self._load_history = []
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self._current_load = 0
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self._last_adjustment = 0
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self._adjustment_cooldown = 30 # 调整冷却时间30秒
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def record_task_interval(self, interval: float):
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"""记录任务间隔，更新负载历史"""
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if len(self._load_history) >= LOAD_HISTORY_SIZE:
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self._load_history.pop(0)
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self._load_history.append(interval)
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# 计算当前负载
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if len(self._load_history) >= 2:
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recent_intervals = self._load_history[-10:] # 最近10个任务
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avg_interval = sum(recent_intervals) / len(recent_intervals)
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# 负载越高，间隔越短
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self._current_load = 1.0 / max(avg_interval, 0.1)
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def should_adjust_timeout(self) -> bool:
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"""判断是否应该调整超时配置"""
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if not ADAPTIVE_CONFIG:
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return False
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current_time = time.time()
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if current_time - self._last_adjustment < self._adjustment_cooldown:
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return False
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return len(self._load_history) >= 10 # 至少需要10个数据点
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def calculate_optimal_idle_timeout(self) -> int:
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"""基于历史负载计算最优空闲超时"""
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if not self._load_history:
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return BROWSER_IDLE_TIMEOUT
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# 计算最近任务间隔的平均值
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recent_intervals = self._load_history[-20:] # 最近20个任务
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if len(recent_intervals) < 2:
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return BROWSER_IDLE_TIMEOUT
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avg_interval = sum(recent_intervals) / len(recent_intervals)
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# 根据负载动态调整超时
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# 高负载时缩短超时，低负载时延长超时
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if self._current_load > 2.0: # 高负载
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optimal_timeout = min(avg_interval * 1.5, 600) # 最多10分钟
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elif self._current_load < 0.5: # 低负载
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optimal_timeout = min(avg_interval * 3.0, 1800) # 最多30分钟
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else: # 正常负载
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optimal_timeout = min(avg_interval * 2.0, 900) # 最多15分钟
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return max(int(optimal_timeout), 60) # 最少1分钟
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def get_optimal_queue_timeout(self) -> int:
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"""获取最优队列超时"""
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if not self._load_history:
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return TASK_QUEUE_TIMEOUT
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# 根据任务频率调整队列超时
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if self._current_load > 2.0: # 高负载时减少等待
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return max(TASK_QUEUE_TIMEOUT // 2, 3)
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elif self._current_load < 0.5: # 低负载时可以增加等待
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return min(TASK_QUEUE_TIMEOUT * 2, 30)
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else:
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return TASK_QUEUE_TIMEOUT
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def record_adjustment(self):
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"""记录一次调整操作"""
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self._last_adjustment = time.time()
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class BrowserWorker(threading.Thread):
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"""截图工作线程 - 每个worker维护自己的执行环境"""
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def __init__(
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self,
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worker_id: int,
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task_queue: queue.Queue,
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log_callback: Optional[Callable] = None,
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pre_warm: bool = False,
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):
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super().__init__(daemon=True)
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self.worker_id = worker_id
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self.task_queue = task_queue
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self.log_callback = log_callback
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self.browser_instance = None
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self.running = True
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self.idle = True
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self.total_tasks = 0
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self.failed_tasks = 0
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self.pre_warm = pre_warm
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self.last_activity_ts = 0.0
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self.task_start_time = 0.0
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# 初始化自适应资源管理器
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if ADAPTIVE_CONFIG:
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self._adaptive_mgr = AdaptiveResourceManager()
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else:
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self._adaptive_mgr = None
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def log(self, message: str):
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"""日志输出"""
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if self.log_callback:
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self.log_callback(f"[Worker-{self.worker_id}] {message}")
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else:
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print(f"[截图池][Worker-{self.worker_id}] {message}")
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def _create_browser(self):
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"""创建截图执行环境（逻辑占位，无需真实浏览器）"""
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created_at = time.time()
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self.browser_instance = {
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"created_at": created_at,
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"use_count": 0,
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"worker_id": self.worker_id,
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}
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self.last_activity_ts = created_at
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self.log("截图执行环境就绪")
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return True
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def _close_browser(self):
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"""关闭截图执行环境"""
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if self.browser_instance:
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self.log(f"执行环境已释放（共处理{self.browser_instance.get('use_count', 0)}个任务）")
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self.browser_instance = None
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def _check_browser_health(self) -> bool:
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"""检查执行环境是否就绪"""
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return bool(self.browser_instance)
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def _ensure_browser(self) -> bool:
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"""确保执行环境可用"""
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if self._check_browser_health():
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return True
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self.log("执行环境不可用，尝试重新创建...")
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self._close_browser()
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return self._create_browser()
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def run(self):
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"""工作线程主循环 - 按需启动执行环境模式"""
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if self.pre_warm:
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self.log("Worker启动（预热模式，启动即准备执行环境）")
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else:
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self.log("Worker启动（按需模式，等待任务时不占用资源）")
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if self.pre_warm and not self.browser_instance:
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self._create_browser()
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self.pre_warm = False
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while self.running:
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try:
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# 允许运行中触发预热（例如池在初始化后调用 warmup）
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if self.pre_warm and not self.browser_instance:
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self._create_browser()
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self.pre_warm = False
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# 从队列获取任务（带超时，以便能响应停止信号和空闲检查）
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self.idle = True
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# 使用自适应队列超时
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queue_timeout = (
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self._adaptive_mgr.get_optimal_queue_timeout() if self._adaptive_mgr else TASK_QUEUE_TIMEOUT
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)
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try:
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task = self.task_queue.get(timeout=queue_timeout)
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except queue.Empty:
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# 检查是否需要释放空闲的执行环境
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if self.browser_instance and self.last_activity_ts > 0:
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idle_time = time.time() - self.last_activity_ts
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# 使用自适应空闲超时
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optimal_timeout = (
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self._adaptive_mgr.calculate_optimal_idle_timeout()
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if self._adaptive_mgr
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else BROWSER_IDLE_TIMEOUT
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)
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if idle_time > optimal_timeout:
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self.log(f"空闲{int(idle_time)}秒（优化超时:{optimal_timeout}秒），释放执行环境")
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self._close_browser()
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continue
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self.idle = False
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if task is None: # None作为停止信号
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self.log("收到停止信号")
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break
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# 按需创建或确保执行环境可用
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browser_ready = False
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for attempt in range(2):
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if self._ensure_browser():
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browser_ready = True
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break
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if attempt < 1:
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self.log("执行环境创建失败，重试...")
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time.sleep(0.5)
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if not browser_ready:
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retry_count = int(task.get("retry_count", 0) or 0) if isinstance(task, dict) else 0
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if retry_count < 1 and isinstance(task, dict):
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task["retry_count"] = retry_count + 1
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try:
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self.task_queue.put(task, timeout=1)
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self.log("执行环境不可用，任务重新入队")
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except queue.Full:
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self.log("任务队列已满，无法重新入队，任务失败")
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callback = task.get("callback")
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if callable(callback):
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callback(None, "执行环境不可用")
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self.total_tasks += 1
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self.failed_tasks += 1
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continue
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self.log("执行环境不可用，任务失败")
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callback = task.get("callback") if isinstance(task, dict) else None
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if callable(callback):
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callback(None, "执行环境不可用")
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self.total_tasks += 1
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self.failed_tasks += 1
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continue
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# 执行任务
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task_func = task.get("func")
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task_args = task.get("args", ())
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task_kwargs = task.get("kwargs", {})
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callback = task.get("callback")
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self.total_tasks += 1
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# 确保browser_instance存在后再访问
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if self.browser_instance is None:
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self.log("执行环境不可用，任务失败")
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if callable(callback):
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callback(None, "执行环境不可用")
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self.failed_tasks += 1
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continue
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self.browser_instance["use_count"] += 1
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self.log(f"开始执行任务（第{self.browser_instance['use_count']}次执行）")
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# 记录任务开始时间
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task_start_time = time.time()
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try:
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# 将执行环境实例传递给任务函数
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result = task_func(self.browser_instance, *task_args, **task_kwargs)
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callback(result, None)
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self.log(f"任务执行成功")
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# 记录任务完成并更新负载历史
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task_end_time = time.time()
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task_interval = task_end_time - task_start_time
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if self._adaptive_mgr:
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self._adaptive_mgr.record_task_interval(task_interval)
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self.last_activity_ts = time.time()
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except Exception as e:
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self.log(f"任务执行失败: {e}")
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callback(None, str(e))
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self.failed_tasks += 1
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self.last_activity_ts = time.time()
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# 任务失败后，检查执行环境健康
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if not self._check_browser_health():
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self.log("任务失败导致执行环境异常，将在下次任务前重建")
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self._close_browser()
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# 定期重启执行环境，释放可能累积的资源
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if self.browser_instance and BROWSER_MAX_USE_COUNT > 0:
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if self.browser_instance.get("use_count", 0) >= BROWSER_MAX_USE_COUNT:
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self.log(f"执行环境已复用{self.browser_instance['use_count']}次，重启释放资源")
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self._close_browser()
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except Exception as e:
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self.log(f"Worker出错: {e}")
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time.sleep(1)
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# 清理资源
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self._close_browser()
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self.log(f"Worker停止（总任务:{self.total_tasks}, 失败:{self.failed_tasks}）")
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def stop(self):
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"""停止worker"""
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self.running = False
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class BrowserWorkerPool:
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"""截图工作线程池"""
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def __init__(self, pool_size: int = 3, log_callback: Optional[Callable] = None):
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self.pool_size = pool_size
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self.log_callback = log_callback
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maxsize = TASK_QUEUE_MAXSIZE if TASK_QUEUE_MAXSIZE > 0 else 0
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self.task_queue = queue.Queue(maxsize=maxsize)
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self.workers = []
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self.initialized = False
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self.lock = threading.Lock()
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def log(self, message: str):
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"""日志输出"""
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if self.log_callback:
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self.log_callback(message)
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else:
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print(f"[截图池] {message}")
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def initialize(self):
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"""初始化工作线程池（按需模式，默认预热1个执行环境）"""
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with self.lock:
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if self.initialized:
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return
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self.log(f"正在初始化截图线程池（{self.pool_size}个worker，按需启动执行环境）...")
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for i in range(self.pool_size):
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worker = BrowserWorker(
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worker_id=i + 1,
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task_queue=self.task_queue,
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log_callback=self.log_callback,
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pre_warm=(i < 1),
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)
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worker.start()
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self.workers.append(worker)
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self.initialized = True
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self.log(f"[OK] 截图线程池初始化完成（{self.pool_size}个worker就绪，执行环境将在有任务时按需启动）")
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# 初始化完成后，默认预热1个执行环境，降低容器重启后前几批任务的冷启动开销
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self.warmup(1)
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def warmup(self, count: int = 1) -> int:
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"""预热截图线程池 - 预创建指定数量的执行环境"""
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if count <= 0:
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return 0
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if not self.initialized:
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self.log("警告：线程池未初始化，无法预热")
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return 0
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with self.lock:
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target_workers = list(self.workers[: min(count, len(self.workers))])
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self.log(f"预热截图线程池（预创建{len(target_workers)}个执行环境）...")
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for worker in target_workers:
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if not worker.browser_instance:
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worker.pre_warm = True
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# 等待预热完成（最多等待20秒，避免阻塞过久）
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deadline = time.time() + 20
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while time.time() < deadline:
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warmed = sum(1 for w in target_workers if w.browser_instance)
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if warmed >= len(target_workers):
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break
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time.sleep(0.1)
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warmed = sum(1 for w in target_workers if w.browser_instance)
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self.log(f"[OK] 截图线程池预热完成（{warmed}个执行环境就绪）")
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return warmed
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def submit_task(self, task_func: Callable, callback: Callable, *args, **kwargs) -> bool:
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"""
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提交任务到队列
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Args:
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task_func: 任务函数，签名为 func(browser_instance, *args, **kwargs)
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callback: 回调函数，签名为 callback(result, error)
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*args, **kwargs: 传递给task_func的参数
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Returns:
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是否成功提交
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"""
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if not self.initialized:
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self.log("警告：线程池未初始化")
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return False
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task = {
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"func": task_func,
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"args": args,
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"kwargs": kwargs,
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"callback": callback,
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"retry_count": 0,
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}
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try:
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self.task_queue.put(task, timeout=1)
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return True
|
||
except queue.Full:
|
||
self.log(f"警告：任务队列已满（maxsize={self.task_queue.maxsize}），拒绝提交任务")
|
||
return False
|
||
|
||
def get_stats(self) -> Dict[str, Any]:
|
||
"""获取线程池统计信息"""
|
||
workers = list(self.workers or [])
|
||
idle_count = sum(1 for w in workers if getattr(w, "idle", False))
|
||
total_tasks = sum(int(getattr(w, "total_tasks", 0) or 0) for w in workers)
|
||
failed_tasks = sum(int(getattr(w, "failed_tasks", 0) or 0) for w in workers)
|
||
|
||
worker_details = []
|
||
for w in workers:
|
||
browser_instance = getattr(w, "browser_instance", None)
|
||
browser_use_count = 0
|
||
browser_created_at = None
|
||
if isinstance(browser_instance, dict):
|
||
browser_use_count = int(browser_instance.get("use_count", 0) or 0)
|
||
browser_created_at = browser_instance.get("created_at")
|
||
|
||
worker_details.append(
|
||
{
|
||
"worker_id": getattr(w, "worker_id", None),
|
||
"idle": bool(getattr(w, "idle", False)),
|
||
"has_browser": bool(browser_instance),
|
||
"total_tasks": int(getattr(w, "total_tasks", 0) or 0),
|
||
"failed_tasks": int(getattr(w, "failed_tasks", 0) or 0),
|
||
"browser_use_count": browser_use_count,
|
||
"browser_created_at": browser_created_at,
|
||
"last_active_ts": float(getattr(w, "last_activity_ts", 0) or 0),
|
||
"thread_alive": bool(getattr(w, "is_alive", lambda: False)()),
|
||
}
|
||
)
|
||
|
||
return {
|
||
"pool_size": self.pool_size,
|
||
"idle_workers": idle_count,
|
||
"busy_workers": max(0, len(workers) - idle_count),
|
||
"queue_size": self.task_queue.qsize(),
|
||
"total_tasks": total_tasks,
|
||
"failed_tasks": failed_tasks,
|
||
"success_rate": f"{(total_tasks - failed_tasks) / total_tasks * 100:.1f}%" if total_tasks > 0 else "N/A",
|
||
"workers": worker_details,
|
||
"timestamp": time.time(),
|
||
}
|
||
|
||
def wait_for_completion(self, timeout: Optional[float] = None):
|
||
"""等待所有任务完成"""
|
||
start_time = time.time()
|
||
while not self.task_queue.empty():
|
||
if timeout and (time.time() - start_time) > timeout:
|
||
self.log("等待超时")
|
||
return False
|
||
time.sleep(0.5)
|
||
|
||
# 再等待一下确保正在执行的任务完成
|
||
time.sleep(2)
|
||
return True
|
||
|
||
def shutdown(self):
|
||
"""关闭线程池"""
|
||
self.log("正在关闭工作线程池...")
|
||
|
||
# 发送停止信号
|
||
for _ in self.workers:
|
||
self.task_queue.put(None)
|
||
|
||
# 等待所有worker停止
|
||
for worker in self.workers:
|
||
worker.join(timeout=10)
|
||
|
||
self.workers.clear()
|
||
self.initialized = False
|
||
self.log("[OK] 工作线程池已关闭")
|
||
|
||
|
||
# 全局实例
|
||
_global_pool: Optional[BrowserWorkerPool] = None
|
||
_pool_lock = threading.Lock()
|
||
|
||
|
||
def get_browser_worker_pool(pool_size: int = 3, log_callback: Optional[Callable] = None) -> BrowserWorkerPool:
|
||
"""获取全局截图工作线程池（单例）"""
|
||
global _global_pool
|
||
|
||
with _pool_lock:
|
||
if _global_pool is None:
|
||
_global_pool = BrowserWorkerPool(pool_size=pool_size, log_callback=log_callback)
|
||
_global_pool.initialize()
|
||
|
||
return _global_pool
|
||
|
||
|
||
def init_browser_worker_pool(pool_size: int = 3, log_callback: Optional[Callable] = None):
|
||
"""初始化全局截图工作线程池"""
|
||
get_browser_worker_pool(pool_size=pool_size, log_callback=log_callback)
|
||
|
||
|
||
def _shutdown_pool_when_idle(pool: BrowserWorkerPool) -> None:
|
||
try:
|
||
pool.wait_for_completion(timeout=60)
|
||
except Exception:
|
||
pass
|
||
try:
|
||
pool.shutdown()
|
||
except Exception:
|
||
pass
|
||
|
||
|
||
def resize_browser_worker_pool(pool_size: int, log_callback: Optional[Callable] = None) -> bool:
|
||
"""调整截图线程池并发（新任务走新池，旧池空闲后自动关闭）"""
|
||
global _global_pool
|
||
|
||
try:
|
||
target_size = max(1, int(pool_size))
|
||
except Exception:
|
||
target_size = 1
|
||
|
||
with _pool_lock:
|
||
old_pool = _global_pool
|
||
if old_pool and int(getattr(old_pool, "pool_size", 0) or 0) == target_size:
|
||
return False
|
||
effective_log_callback = log_callback or (getattr(old_pool, "log_callback", None) if old_pool else None)
|
||
_global_pool = BrowserWorkerPool(pool_size=target_size, log_callback=effective_log_callback)
|
||
_global_pool.initialize()
|
||
|
||
if old_pool:
|
||
threading.Thread(target=_shutdown_pool_when_idle, args=(old_pool,), daemon=True).start()
|
||
|
||
return True
|
||
|
||
|
||
def shutdown_browser_worker_pool():
|
||
"""关闭全局截图工作线程池"""
|
||
global _global_pool
|
||
|
||
with _pool_lock:
|
||
if _global_pool:
|
||
_global_pool.shutdown()
|
||
_global_pool = None
|
||
|
||
|
||
if __name__ == "__main__":
|
||
# 测试代码
|
||
print("测试截图工作线程池...")
|
||
|
||
def test_task(browser_instance, url: str, task_id: int):
|
||
"""测试任务：访问URL"""
|
||
print(f"[Task-{task_id}] 开始访问: {url}")
|
||
time.sleep(2) # 模拟截图耗时
|
||
return {"task_id": task_id, "url": url, "status": "success"}
|
||
|
||
def test_callback(result, error):
|
||
"""测试回调"""
|
||
if error:
|
||
print(f"任务失败: {error}")
|
||
else:
|
||
print(f"任务成功: {result}")
|
||
|
||
# 创建线程池（2个worker）
|
||
pool = BrowserWorkerPool(pool_size=2)
|
||
pool.initialize()
|
||
|
||
# 提交4个任务
|
||
for i in range(4):
|
||
pool.submit_task(test_task, test_callback, f"https://example.com/{i}", i + 1)
|
||
|
||
print("\n任务已提交，等待完成...")
|
||
pool.wait_for_completion()
|
||
|
||
print("\n统计信息:", pool.get_stats())
|
||
|
||
# 关闭线程池
|
||
pool.shutdown()
|
||
print("\n测试完成！")
|